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Linking Brain Responses to Naturalistic Music Through Analysis of Ongoing EEG and Stimulus Features.

, , , , , , , , , , and . IEEE Trans. Multim., 15 (5): 1060-1069 (2013)

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From Vivaldi to Beatles and back: Predicting lateralized brain responses to music., , , , , , , and . NeuroImage, (2013)The chronnectome of musical beat., , , , and . NeuroImage, (2020)Predicting Individual Differences from Brain Responses to Music: A Comparison of Functional Connectivity Measures., , and . BI, volume 13974 of Lecture Notes in Computer Science, page 191-202. Springer, (2023)Differential Effects of Trait Empathy on Functional Network Centrality., , , , and . BI, volume 12241 of Lecture Notes in Computer Science, page 107-117. Springer, (2020)Dimension reduction for individual ica to decompose FMRI during real-world experiences: principal component analysis vs. canonical correlation analysis., , , , , , , and . ESANN, (2013)Towards Multimodal MIR: Predicting individual differences from music-induced movement., , , , and . ISMIR, page 54-61. (2020)Generation of stimulus features for analysis of FMRI during natural auditory experiences., , , , , , and . EUSIPCO, page 2490-2494. IEEE, (2014)Semi-blind independent component analysis of functional MRI elicited by continuous listening to music., , , , , , , and . ICASSP, page 1310-1314. IEEE, (2013)Tag2Risk: Harnessing Social Music Tags for Characterizing Depression Risk., , , , and . ISMIR, page 384-391. (2020)Sonus Texere! Automated Dense Soundtrack Construction for Books using Movie Adaptations., , and . ISMIR, page 535-542. (2022)